GIM

About GIM

Grace Investment Machine (GIM) is an agentic investing lab developing autonomous AI systems for capital markets. Founded in July 2025 by Xu Jiahao and Dr. Liu Qi, the company aims to create a new category of asset management by replacing human portfolio managers with specialized AI agents. These agents are designed to allocate capital, monitor risk, and learn continuously from global markets, inspired by the long-term, disciplined approach of Berkshire Hathaway. In March 2026, the company secured tens of millions of yuan in an angel funding round co-led by Monolith and Wuyuan Capital to advance its large financial model, data infrastructure, and team expansion.

The founding team combines expertise in investment and advanced AI research. Xu Jiahao has over a decade of experience in capital markets, having served as a senior investor at Neumann Advisors and Wuyuan Capital. Dr. Liu Qi is an assistant professor in the Department of Computer Science at the University of Hong Kong, with research experience at DeepMind and Meta (formerly Facebook AI Research), focusing on multi-modal large models for complex reasoning. The core team includes members from top hedge funds and leading AI companies like DeepMind, Meta, and Anthropic.

GIM's core technology is a self-evolving intelligent agent investment platform built on a multi-agent architecture. The company has developed a proprietary large financial time-series model trained on high-frequency market data to model market dynamics, predict returns, and optimize factor combinations. This system supports the engineering deployment of AI strategies, including model version control, automated training, and real-time simulation. The firm emphasizes a conservative culture with a focus on governance and safety, treating model changes with rigorous testing and documentation to ensure transparent and auditable decision-making. GIM does not solicit public investment; its website is primarily informational, aimed at attracting potential collaborators and team members.